Are the Columns of Matrix A Linearly Independent?

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In summary, the conversation discusses the concepts of vector spaces, linear independence, and subspaces in linear algebra. The first question asks to find Cartesian equations for the column space and null space of a given matrix A. The second question asks to prove a property in any vector space. The third question discusses the set of 2x2 matrices and its subset of diagonal matrices, and asks to provide examples and prove the subset is a subspace of the original set.
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Q1:
Let A =
1 3 0
0 -4 4
3 4 5

a) Find Cartesian equations for Col(A) and Null(A).
b) Are the columns of A linearly independent? Give full reasons for your answer (based on
the definition of linear independence).

Q2: Prove that in any vector space k × 0 = 0, where k is any real number and 0 is the zero vector.

Q3:
The set M2,2 of 2 × 2 matrices, with real entries, is a vector space.
The set of diagonal matrices D =
[(a 0
0 b) | a, b 2 E R is a subset of M2,2
a) Write down two particular matrices which belong to D, and two particular matrices which
belong to M2,2 but not to D.
b) Prove that D is a subspace of M2,2
 
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FAQ: Are the Columns of Matrix A Linearly Independent?

What are matrices and vectors?

Matrices and vectors are mathematical objects used to represent and manipulate data in various fields such as physics, engineering, and computer science. A matrix is a rectangular array of numbers or symbols, while a vector is a one-dimensional array of numbers or symbols.

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What is the difference between a row vector and a column vector?

A row vector is a matrix with a single row, while a column vector is a matrix with a single column. In other words, a row vector is a horizontal array, while a column vector is a vertical array.

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